JP

Protection of Coastal Infrastructure under Rising Flood Risk

The 2005 hurricane season was particularly damaging to the United States, contributing to significant losses to energy infrastructure—much of it the result of flooding from storm surge during hurricanes Katrina and Rita. In 2012, Hurricane Sandy devastated New York City and Northern New Jersey. Research suggests that these events are not isolated, but rather foreshadow a risk that is to continue and likely increase with a changing climate. Extensive energy infrastructure is located along the U.S. Atlantic and Gulf coasts, and these facilities are exposed to an increasing risk of flooding. We study the combined impacts of anticipated sea level rise, hurricane activity and subsidence on energy infrastructure with a first application to Galveston Bay. Using future climate conditions as projected by four different Global Circulation Models (GCMs), we model the change in hurricane activity from present day climate conditions in response to a climate projected in 2100 under the IPCC A1B emissions scenario. We apply the results from hurricane runs from each model to the SLOSH model to investigate the projected change in frequency and distribution of surge heights across climates. Further, we incorporate uncertainty surrounding the magnitude of sea level rise and subsidence, resulting in more detailed projections of risk levels for energy infrastructure over the next century. Applying this model of changing risk exposure, we apply a dynamic programming cost-benefit analysis to the adaptation decision.

Quantifying Emissions of Greenhouse Gases from South Asia Through a Targeted Measurement Campaign

Methane (CH4), nitrous oxide (N2O) and sulfur hexafluoride (SF6) are powerful greenhouse gases with global budgets that are well-known but regional distributions that are not adequately constrained for the purposes of mitigation and policy initiatives. Quantifying emissions using inverse approaches at the national scale requires measurements that specifically target the region of interest. Primarily due to the lack of atmospheric measurements from the region, emissions estimates of these greenhouse gases from India have largely been missing.

New in situ measurements of atmospheric mole fractions from a Himalayan station in Darjeeling, India (27.03N, 88.26E, 2200 meters above sea level) have been collected from December 2011 for CH4 and March 2012 for N2O and SF6 to February 2013 using high-precision instrumentation that is linked to the Advanced Global Atmospheric Gases Experiment (AGAGE). These measurements comprise the rest high-frequency dataset of these gases collected in India and are used for measurement-based assessment of emissions. Several features are identified. In SF6, the signal associated with Northern Hemispheric background is typically present. CH4 and N2O mole fractions are almost always enhanced over the background, suggesting strong regional sources. Additionally, a diurnal signal resulting from thermally driven winds is seasonally present.

A particle dispersion model is used to track `air histories' of measurements, quantifying the sensitivity of concentrations at Darjeeling to surface emissions. The effect of topography on the derived air histories is investigated to test the robustness of the model in simulating transport in this complex environment. The newly acquired data set is used to investigate the ability of the model to reproduce signals that stem from the mesoscale diurnal winds. The sensitivities of meteorological resolution and particle release height are investigated to better quantify some of the uncertainties associated with this chemical transport model.

A Quasi-Newton inverse method is used to estimate emissions at monthly resolution. CH4, N2O and SF6 emissions from India are found to be 44.354:2 38:5 Tg yr1 , 8251045 707 GgN yr1 and 221241 205 kton yr1 , respectively. Significant uncertainty reduction is seen on emissions from India during the summer when the monsoon results in high sensitivity over the subcontinent

Quantifying Future Changes in Extreme Precipitation Events Based on Resolved Synoptic Atmospheric Patters

An important question for climate change science is possible shifts in the extremes of regional water cycle, especially changes in patterns, intensity and/or frequency of extreme precipitation events. In this study, an analogue method is developed to help detect extreme precipitation events and their potential changes under future climate regimes without relying on the highly uncertain modeled precipitation. Our approach is based on the use of composite maps to identify the distinct synoptic and large-scale atmospheric conditions that lead to extreme precipitation events at local scales. The analysis of extreme daily precipitation events, exemplified in the south-central United States, is carried out using 62-yr (1948-2010) CPC gridded station data and NASA’s Modern Era Retrospective-analysis for Research and Applications (MERRA). Various aspects of the daily extremes are examined, including their historical ranking, associated common circulation features at upper and lower levels of the atmosphere, and moisture plumes. The scheme is first evaluated for the multiple climate model simulations of the 20th century from Coupled Model Intercomparison Project Phase 5 (CMIP5) archive to determine whether the statistical nature of modeled precipitation events (i.e. the numbers of occurrences over each season) could well correspond to that of the observed. Further, the approach will be applied to the CMIP5 multi-model projections of various climate change scenarios (i.e. Representative Concentration Pathways (RCP) scenarios) in the next century to assess the potential changes in the probability of extreme precipitation events. The research results from this study should be of particular significance to help society develop adaptive strategies and prevent catastrophic losses.

Quantifying Regional Economic Impacts of CO2 Intensity Targets in China

To address rising energy use and CO2 emissions, China’s leadership has enacted energy and CO2 intensity targets under the Twelfth Five-Year Plan (2011–2015), which are defined at both the national and provincial levels. We develop a computable general equilibrium (CGE) model with global coverage that disaggregates China’s 30 provinces and includes energy system detail, and apply it to assess the impact of provincial CO2 emissions intensity targets. We compare the impact of the provincial targets approach to a single national target for China that achieves the same reduction in CO2 emissions intensity at the national level. We find that at the national level, the national target results in 25% lower welfare loss relative to the provincial targets approach. Given that the regional distribution of impacts has been an important consideration in the target-setting process, we focus on the changes in provincial level CO2 emissions intensity, CO2 emissions, energy consumption, and economic welfare. We observe significant heterogeneity across provinces in terms of the energy system response as well as the magnitude and sometimes sign of welfare impacts. We further model the current policy of fixed end-use electricity prices in China and find that national welfare losses increase. Assumptions about capital mobility have a substantial impact on national welfare loss, while assumptions about natural gas resource potential does not have a large effect.

Quantifying the health and economic impacts of mercury: an integrated assessment approach

Mercury is a toxic pollutant that endangers human and ecosystem health. Especially potent in the form of methyl mercury, exposure is known to lead to adverse neurological effects, and, a growing body of evidence suggests, cardiovascular ones. Mercury's health impacts have economic consequences, and benefit-cost analyses focusing on these health benefits are used to motivate regulatory action in the United States and elsewhere. However, many existing valuation studies of the health impacts of mercury have substantial limitations, both from a scientific and economic perspective. Because they do not fully model mercury's path from emissions to impacts, they do not fully reflect the spatial and temporal dimensions of the mercury problem. In addition, many do not consider uncertain, but potentially policy-relevant health effects like cardiovascular disease.

This thesis develops an integrated assessment framework that more completely represents mercury's emissions-to-impacts path, and then evaluates its policy relevance. The assessment framework integrates chemical transport modelling, exposure and health impacts modelling, and general equilibrium modelling of the US economy. As a case study, the framework is used to evaluate the benefits of the Mercury and Air Toxics Standards—a recent US regulation that targets emissions from coal-fired power plants—until 2050. I estimate the annual benefit of MATS to be 13 million 2005 USD, compared to a scenario that includes stringent air quality policy, and 414 million 2005 USD when compared to a no policy scenario. I find that the estimate is highly sensitive to uncertainties along the emissions-to-impacts path—in particular, dose-response parameterization, ecosystem lag times, and discount rate. The analysis suggests that given the large ranges of uncertainty involved, more fully representing the emissions-to-impact chain does not lead to substantially different aggregate benefits estimates, compared to those existing in the literature. However, because this approach does provide more insight into the controlling influences behind benefits, it can inform decisions about where policies should be implemented, and of what type, as well as best practices for transparently assessing mercury-related policies.

Quantifying the Impact of Renewable Energy Futures on Cooling Water Use

This article presents an empirically based model, WiCTS (Withdrawal and Consumption for Thermoelectric Systems), to estimate regional water withdrawals and consumption implied by any electricity generation portfolio. WiTCS uses water use rates, developed at the substate level, to predict water use by scaling the rates with predicted energy generation. The capability of WiCTS is demonstrated by assessing the impact of renewable electricity generation scenarios on water use in the United States (U.S.) through 2050. The energy generation scenarios are taken from the Renewable Energy Futures Study performed by the U.S. National Renewable Energy Laboratory of the U.S. Department of Energy. Results indicate reductions in water use are achieved under these renewable energy scenarios. The analysis further explores the impact of two modifications to the modeling framework. The first modification presumes geothermal and concentrated solar power generation technologies employ water-intensive cooling systems vs. cooling technology that requires no water. The second modification presumes all water-intensive cooling technologies use closed cycle cooling (as opposed to once-through cooling) technologies by 2050. Results based on one of the renewable generation scenarios indicate water use increases by over 20% under the first modification, and water consumption increases by approximately 40% while water withdrawals decrease by over 85% under the second modification.

© 2014 American Water Resources Association

Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach

The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, we present a technique that extends the latitudinal projections of the 2-D atmospheric model of the MIT Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate-model projections archived from exercises carried out for the 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and we demonstrate this approach in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, we characterize the climate models' spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of meta-ensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate-model projections. This hybridization of the climate-model longitudinal projections with the global and latitudinal patterns projected by the IGSM can, in principle, be applied to any given state or flux variable that has the sufficient observational and model-based information.

© 2012 American Meteorological Society

Quantifying the role of land use change and land management in ecosystem function for the U.S. using the Terrestrial Ecosystem Model

Recent research has confirmed the importance of secondary vegetation regrowth and land management in the terrestrial carbon cycle. Reforestation in temperate regions, especially in eastern North America, has contributed to reduced warming. However, there is uncertainty in model estimates of these secondary land fluxes and the role of land use management factors such as shifting cultivation, irrigation and fertilization. The goal of this work is to explore the role of agricultural conversion/abandonment, wood harvesting, nitrogen fertilization, irrigation, and tillage, within the context of rising CO2 levels, warming climate, nitrogen deposition and ozone on ecosystem carbon and water dynamics using the process-based prognostic Terrestrial Ecosystem Model (TEM) – Hydro2 with the historical land cover transition dataset of Hurtt et al. (2006). The new version of TEM-Hydro2 includes multiple vegetation structural pools, enhanced disturbance modules and calibration, and a reduced-form open nitrogen model. We consider three experiments to explore historical terrestrial carbon dynamics for 1900-2006 in the U.S.: 1) potential vegetation, 2) transient vegetation based on the Hurtt et al. (2006) dataset including realistic agricultural management, and 3) same as previous case without the agricultural management. A preliminary simulation was run for a single pixel (0.5-degree) in the vicinity of Harvard Forest in MA using Ramankutty and Foley’s (1999) data, which contains 6% cropland in 1900, abandoned by the end of the century. This result shows that the process of cropland establishment and abandonment reduces 5.2% of annual NPP and 41.8% of cumulative NEP, reducing the strength of today’s carbon sink. Annual average runoff increased 6.1% and soil moisture 2.2% as a result of including past disturbance. We will present results extrapolated across the entire U.S. with the Hurtt et al. (2006) dataset for the three scenarios we outlined above.

Quantifying Uncertainty in Changes in Storm Tracks Associated with Climate Change

Changes in extratropical storm tracks associated with climate change can directly affect the transport of momentum, energy and water vapor as well as impact the carbon cycle and modify the ocean circulation. For these reasons quantifying the possible range of changes in storm-track intensity is very relevant. In this paper, we analyze the transient eddy kinetic energy from six simulations using the MIT IGSM-CAM framework. The MIT IGSM-CAM framework links the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM) version 3 to the MIT Integrated Global System Model (IGSM) version 2.3, an intermediate complexity fully coupled earth system model that allows simulation of critical feedbacks among its various components, including the atmosphere (represented by a zonal-mean statistical-dynamical model), ocean, land, urban processes and human activities. An essential feature of the MIT IGSM-CAM is the flexibility to vary the climate parameters of the framework (climate sensitivity, net aerosol forcing and ocean heat uptake rate). The simulations presented in this paper were carried out for two emission scenarios (a “Business as usual” scenario and a 660 ppm of CO2-eq stabilization) and three sets of climate parameters. The three values of climate sensitivity chosen are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the observed 20th century climate change with simulations by the IGSM with a wide range of climate parameters values. The associated aerosol forcing values were chosen to ensure a good agreement of the simulations with the observed climate change over the 20th century. Because the concentrations of sulfate aerosols significantly decrease over the 21st century in both emissions scenarios, climate changes obtained in these six simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

Quantifying Uncertainty in the Uptake of Heat and Carbon in the 21st Century

The uptake of heat and carbon is examined in an ensemble of runs using an Earth System Model of intermediate complexity. Climate model “parameters” varied to produce the ensemble are the climate sensitivity, the aerosol forcing, and the strength of ocean background diapycnal mixing. Joint probability distributions for climate sensitivity and aerosol forcing are constructed by comparing climate model results from 20th century simulations with available observational data. The results from the 21st century ensemble allows us to construct probabilistic distributions for changes in important climate change variables such as surface air temperature, sea level rise, magnitude of the meridional overturning circulation, air-sea fluxes of carbon, distribution of nutrients, and the export of carbon to the deep ocean. We use the different dynamical and thermal structures of the ensemble members as a tool to explore the controls on and the uncertainty in heat and carbon uptake.

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